1. Field of the Invention
The present invention relates, in general, to resource management, and, more particularly, to software, systems and methods for matching human resources to human resource needs of an organization.
2. Relevant Background
The world economy is characterized by a scarcity of skilled human resources for a variety of jobs. As the educational and experience requirements increase in a technological society, the pool of people having necessary and desired skills becomes smaller. This creates a situation in which many jobs are chasing fewer and fewer skilled workers. This is complicated in many industries, employees tend to move from job to job every few years. This is particularly true of skilled employees and even more particularly true in the information technologies industries. An advantage in identifying, obtaining and managing employees represents a significant strategic advantage for an organization.
It is increasingly difficult for employers to identify and hire qualified employees and contractors for particular positions. Human resource needs often arise suddenly and unpredictably, but must be filled quickly. With product development cycles and product life cycles becoming shorter, personnel with needed skills must be identified and hired quickly. At the same time, each candidate and position must be sufficiently analyzed to make meaningful decisions.
Job matching systems tend to be modeled after bulletin boards where available positions and/or applicants are posted and the other party must periodically peruse or search through the postings. This is inefficient because the participants are only made aware of other participants at the instant they conduct a search or log on. A new job applicant that registers moments after a search was performed will not be reported to the searching party, for example. Hence, participants must access the system frequently and conduct searches to obtain up-to-date information.
Search-based systems have limited ability to deal with the various words, terms and syntax used in the postings. A given job posting, for example, is amenable to a variety of expressions and it is difficult, even with natural language search engines, to effectively search through the various listings and leave with certainty that the most relevant matches have been found by the search engine. Many words and terms in the English language, when viewed in context, imply much more than the word's literal definition. Strict text-based matching used by search engines miss these implications. Even fuzzy matching, which is often based upon a word's syntax, synonyms, antonyms and the like, tend to miss complex meanings that are implied by simple words and the context in which they are used. For example, a job applicant may express that they have Java programming experience, which a typical search tool will match with job descriptions that call for Java experience. However, such experience implies that the applicant has object-oriented programming knowledge which would not be identified by conventional search engines and fuzzy matching techniques. A need exists for a system and method that overcomes the limitations of search-based systems to detect, imply, and deduce matches in a context-sensitive manner.
Another limitation of conventional systems is that even where an applicant's abilities and skills are accurately expressed, there is no way for the applicant to express a desire to use those skills in future employment. To retain workers it is desirable to find workers that are interested in the job and interested in the skills required by the job. For example, a person may be a skilled Cobol programmer, but uninterested in taking a position that uses those skills. Conventional worker identification systems do not consider worker interests and desires and so risk creating job matches that will be difficult to manage and maintain over time.
In-person job matching through conventional interviews and negotiation is inefficient, time consuming, and expensive. Also, it tends to be biased as the participants may express different needs and desires in an attempt to satisfy perceived requirements of the other party. This bias can result in sub-optimal matching of human resources to human resource needs.
A need also exists for systems and software that provide services beyond the identification and matching of potential candidates to job openings. Once a match is defined the life cycle of a typical hiring process continues through negotiations, travel, interviews, testing, and contracting among other steps. These steps are typically managed manually using lists or personal information management products. Hence, a need exists for providing follow-up on services to manage the hiring process in an integrated fashion.